AI/ML Software Developer

4 days ago

Jodhpur, Rajasthan, India beBeeEmbedded Full time ₹ 80,00,000 - ₹ 1,20,00,000
Embedded AI Software Engineer

We're seeking a talented Embedded AI Software Engineer to join our innovative team. As an expert in the field, you'll play a pivotal role in designing, implementing, and optimizing embedded software solutions for AI/ML workloads.

Key Responsibilities:
  • LINUX Expertise: Configure and manage Linux environments (Ubuntu and custom distributions), including kernel modules, system tuning, cross-compilation, and deployment scripts.
  • AI/ML Optimization and Testing on the Edge: Integrate ML models into embedded systems; collaborate with Data Science teams to enable deployment on resource-constrained hardware.
  • Low-Level Engineering: Work with C, C++, and Python to build and optimize drivers, OS-level services, and low-level libraries for ML acceleration.
  • Containerization: Develop, test, and optimize Dockerized applications for AI/ML workloads, ensuring portability, efficiency, and compliance with partner satellite company requirements.
  • Embedded Systems Ownership: Manage and maintain Edge AI development kits (NVIDIA Jetson, Xilinx platforms, etc.), ensuring smooth workflows for in-orbit simulation and testing.
  • Hardware Acceleration: Leverage CUDA, cuDNN, TensorRT (NVIDIA) and Vitis AI / OpenCL (Xilinx) to accelerate workloads.
  • Systems Integration: Interface with satellite payload hardware and ground systems; debug integration issues across hardware, OS, and application layers.
  • Ci/Cd for Edge: Develop pipelines for automated testing and deployment of embedded software builds.
  • Documentation & Support: Maintain clear documentation of configurations, workflows, and deployment practices; support partner satellite companies in deploying our dockerized products.
  • Version Control & Collaboration: Git/GitHub, code review best practices, and working in distributed development teams.
Required Skills:
  • Networking & Protocols: Knowledge of embedded networking (TCP/IP, UDP, MQTT, gRPC), especially for low-bandwidth or intermittent links.
  • Security & Encryption: Familiarity with secure boot, encryption standards, and container security.
  • Cross-Platform Development: Experience with ARM/x86 toolchains, cross-compilation, and Yocto/OpenEmbedded.
  • Performance Optimization: Ability to profile embedded workloads and optimize for power, latency, and throughput constraints.
  • Scripting & Automation: Bash, Python, and Ansible for automating builds, deployments, and system monitoring.
  • Debugging & Profiling Tools: GDB, Valgrind, perf, Nsight, and similar tools for low-level performance analysis.
  • Satellite/Space Domain Exposure: Experience with telemetry, satellite communications, or aerospace-grade systems.
Benefits:
  • Reliable, efficient Dockerized builds delivered to partner satellites.
  • Smooth operation and maintenance of NVIDIA/Xilinx dev kits for AI/ML use cases.
  • Reduced latency and improved efficiency of ML models on embedded devices.
  • Strong cross-team collaboration leading to faster turnaround on edge deployment milestones.

At our organization, we believe in equal opportunity employment and welcome applicants without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

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